A/B testing in ASO: the basics and beyond

A/B testing can lead to double-digit uplift in your conversion rate when applied correctly to your app store optimization (ASO) efforts—helping you turn more app store page visitors into installs. And yet, many marketers feel frustrated by A/B testing because they don’t have the right foundation in place.

In this blog, we’ll review A/B testing basics for ASO and then dive into the top strategies I’ve developed during my years as an ASO manager in the gaming industry. These are all tips I shared in my latest webinar about Going beyond A/B testing. And as a bonus, you’ll find a downloadable A/B test checklist below to ensure your next test drives results.

Key takeaways

• A/B testing compares variations of your app store assets to boost installs.
• Test both pre-tap (icon, title) and post-tap (screenshots, video) elements.
• Focus on one change per test and tie it to a clear user behavior hypothesis.
• Run tests for at least 7 days to get reliable, week-spanning data.
• Mixing paid and organic traffic can skew A/B test results.
• Reach statistical significance to know if your test result is reliable.
• Use AppTweak to preview tests and monitor competitor A/B strategies.

What is A/B testing for ASO?

A/B testing for ASO is testing two (or more) versions of an element on your app’s page—like different screenshots or icons—to see which one appeals most to store visitors.

You can control how much of your store traffic sees each version of your test, but you can’t choose which types of users, such as visitor intent or demographic factors like age or gender, are included.

Comparing the results of the test, you can then determine which version is most likely to increase your app installs.

The store traffic that can see your A/B tests includes:

• Visitors browsing in the Explore (Google Play) or Browse (App Store) tabs.
• Visitors who find your app through search results.
• Any visitor who visits your app page during the test.

Why is A/B testing important for ASO?

Doing A/B testing lets you make smart, data-driven decisions instead of guessing. Even a 3-5% conversion rate lift can have a major impact at scale.

A/B testing helps you increase your app’s conversion rate, which can indirectly boost your organic visibility by improving install velocity. It’s also a great way to test new features or creatives. Many ASO managers use it to see how users respond to user interface updates or seasonal creatives as well as validate creative changes before a big release.

In short, an A/B test for your mobile app’s ASO should either improve performance or reveal important learnings, thereby removing guesswork.

What to A/B test in ASO?

On both the App Store and Google Play, you can enhance your app’s first impression by testing the elements a user sees before they even tap to learn more about your app.

Pre-tap elements to test:

• App icon: Shapes, colors, visual style, brand emphasis
• App title/Name and Subtitle: Length, clarity, keyword inclusion (only on Google Play via Custom Store Listings)
• Screenshots: Text overlays, background colors, order, layout.
• Promotional video: thumbnail, pacing, text overlays, and visual styles

As these elements appear in the search results, they influence whether or not users tap to view your app store listing and have the biggest impact on tap-through rate (TTR) and conversion rate (CVR).

Post-tap (page) elements to test:
(Most testable via Store Listings Experiments on Google Play)

• Screenshots: Order, layout, text overlays, background colors
• Long description: Messaging structure, keyword density, feature order (Google Play only)
• Feature graphics: Background color/contrast, text vs no text, messaging, CTA (Google Play only)
• Promotional video/preview: Thumbnail, length, messaging, feature order, CTA

These elements affect on-page conversion rate (CVR), meaning they can be the final “push” for a user to download your app. You want to ensure these elements are aligned with what your app will deliver, as that will impact user expectations and ultimately, retention.

For example, Nike tested its screenshots’ background color and found that the bright blue background performed better than the lighter one.

Likely hypothesis: If we use brighter, high-contrast backgrounds in our screenshots, visitors will better engage with the page and be more likely to download the app.

Variable tested: Background color of screenshots

Why test this? Visually engaging designs can grab attention, better highlight core features, and guide users toward conversion.

Best practices for A/B testing your ASO efforts

An A/B test should either teach you something or drive performance. Even ASO professionals can make small mistakes that make their tests unreliable. The following key principles ensure your next A/B test is more trustworthy.

Test one variable at a time

Pick one element—app title, description, screenshot, pricing, etc.—and hypothesize what will happen to user behavior when you make a singular change to that variable.

When you test multiple elements, it can create confusion about what actually caused the result, providing no clear takeaway. You want this test to be easy to replicate or learn from by making one clear change and isolating its impact.

Have a clear hypothesis tied to user behavior

The scientific method is alive and well when it comes to A/B testing. Start with a clear theory about why the change you’re making should influence user behavior. Otherwise, you’re in “trial-and-error” territory.

Let’s go back to Nike’s example hypothesis: If we use brighter backgrounds in our screenshots, users will be more likely to notice the app in search results—leading to more installs.

A good hypothesis like the above should explain what you expect to happen (more installs)—and what that says about your audience (they’re attracted to more high-contrast screenshots). That way, even if the test loses, you still learn something.

Keep your target audience in mind

The broader your tests’ audience, the more mass appeal your creative changes must have to beat the baseline. You can test more effectively if you limit your scope to a specific language, country, or traffic segment.

For example, we have an AppTweak client whose bold and text-heavy screenshots perform well in western markets but underperform in Japan. Japanese users tend to prefer clean, minimalist designs.

Therefore, we recommended they localize their screenshots for the Japanese market to be simple in design and focus on one clear message per image. As a result, they saw a noticeable lift in conversion. So, don’t discount localizing your creatives to match cultural expectations.

Run your test for at least seven days

User behavior varies across weekdays and weekends. Ending a test too early, after two or three days, can lead to misleading results due to temporary fluctuations in traffic, installs, or conversion patterns.

We’ve seen that tests run for fewer than seven days often show “early winners” that reverse after a full week of data. Therefore, we recommend running tests for a minimum of seven days, ideally 14 if you have the traffic. Ensure the test duration is consistent across variants. But most importantly, don’t stop early, even if one variant appears to be “winning” after two days.

Don’t expect identical results across app stores

The appearance of app pages on Google Play differs from on the App Store, as does the behavior of store traffic. Therefore, it’s a mistake to believe that all findings observed on one store apply to both stores without considering differences in user interface or traffic.

To get reliable results, test the assets on both the App Store and Google Play unless you have a valid reason to believe that results should be directly applied to both stores.

Watch your traffic sources

Different traffic sources can have very different behavior patterns. If you’re running paid user acquisition campaigns while testing, this traffic might not behave like organic users.

For example, paid users often arrive with different expectations or motivations. Mixing the two in your test group can lead to skewed results or misleading conclusions. When possible, segment your test or isolate paid and organic traffic to ensure your findings reflect real-world performance.

Use statistical confidence

Reaching statistical significance is key to knowing whether your result is reliable or just random noise.

Google Play defaults to 90% confidence, which is fine for low-risk experiments. But if you’re testing a change that could significantly impact performance—like a new icon or feature graphic—aim for 95% or even 98% confidence.

Higher thresholds reduce the risk of false positives and give you more confidence in applying the winning variation at scale. For more tips on increasing reliability read How to improve A/B tests on Google Play.

Did you find these A/B test best practices helpful? If so, you take them with you by downloading our A/B testing for ASO: The essential checklist.

Publishing your first A/B test (App Store and Google Play)

Once you have established your hypothesis, follow these simple steps:

1. Go to your store console and find its A/B testing tab or page (the “Store Listing Experiments” page for Google Play or the “Product Page Optimization” tab for the App Store).
2. Click on “Create a test/an experiment” and follow the instructions.

You’ll be asked to set up a few parameters before you can publish the test. Here are the most important ones:

• Choosing the traffic proportion (%) that will see one of your variants instead of the original page. At AppTweak, we recommend splitting traffic equally between the original page and the different variants to get the most accurate results.
• Estimating your test duration. This indicative setting allows you to estimate when you believe your A/B test will deliver conclusive results, so you understand whether your expectations were realistic or not. Reaching the end of the estimated test duration won’t end the A/B test.
• Selecting the assets you want to test. As previously explained, it’s better to focus on one element at a time to be able to better measure the impact of the test.

Store listing experiments on Google Play

Store listing experiments are one of the most widely used A/B testing tools for ASO on Google Play. It allows you to test different versions of your app store assets with real traffic to measure which version drives the highest conversion rate.

In the Google Play Console, go to your Store Listing section and click on “Experiments” to create a new test. You can test up to three variants against your current default listing and run the experiment for as long as needed—there’s no fixed end date unless you choose one.

Note: Store Listing Experiments only apply to your app’s main store listing. You cannot run experiments on Custom Store Listings at this time.

Google Play allows you to test most assets on your store listing—creatives such as your icon, promotional video, feature graphic,and  screenshots, as well as your short and long descriptions. Your app’s title, pricing and custom store listing variations cannot be tested.

A/B testing on Google Play allows you to:

• Identify the most impactful elements on your app page.
• Learn what resonates with your target market, based on their language and locality.
• Potentially increase your app’s conversion rate thanks to the insights gained.
• Spot seasonality effects or creative fatigue over time.

App Store product page optimization

Product page optimization (PPO) is a helpful tool for ASO practitioners to understand the impact of different page elements on iOS conversion rates. Apple rolled out PPO with iOS 15 and, as such, PPO variants are only shown to App Store users with iOS 15 or later.

Apple only allows you to test creative assets (icon, preview video, and screenshots) for up to 90 days with PPO. Up to 3 variants can be tested against the original version. You can only run one test per app at a time, but you can run localized tests for all the languages your app supports.

Learn how you can use product page optimization to optimize your App Store assets.

Before starting your A/B test, think through what you want to test and why. For some, revamping screenshots will be the main priority. For others, whether to add an app preview video is the principal concern. Assess which elements of your brand or product matter most to your store traffic and how you can make your app stand out accordingly.

A/B testing and beyond with AppTweak

Now that we’ve talked about properly structuring your A/B tests and how to publish them, here’s how you can take your A/B tests to the next level with AppTweak.

1. Spy on your competitors’ A/B tests

At AppTweak, we’ve developed a feature that allows you to spy on A/B tests performed by your competitors. This can provide valuable information, such as how often your competitors run A/B tests and for how long, the elements of their app page they test most often, and what changes they introduce in their tests.

Find out which metadata elements your competitors are A/B testing with AppTweak’s Timeline. Learn more in our article Spy on your competitors’ A/B tests.

2. See how your A/B test would look before publishing

Don’t risk publishing your A/B test without double-checking how it will look before it goes live. Use AppTweak’s App Page Preview to upload your new creatives. You’ll instantly see how your app page will look in both light mode and dark mode, avoiding any surprises or mistakes that could mess up your test.

3. Go beyond A/B testing with Incrementality Analysis

A/B tests measure direct impact, but they don’t always account for external factors like seasonality, paid acquisition shifts, or organic algorithm changes.

Just because a variation performs well for a short time, doesn’t mean it’s always the best long-term option. Consider which of these tests is best for your hypothesis.

• A/B testing is great for comparing direct changes, such as “Which icon drove a higher conversion rate?”
• Incremental testing determines if a lift in performance was truly caused by your change or if other factors—like paid campaigns or market trends—played a role. You can use AppTweak’s Incrementality Analysis to do this.

Learn more by reading What is incrementality in marketing?

Conclusion

When done well, A/B testing for your mobile app can be an effective tool in your ASO toolkit. It helps you eliminate guesswork, uncover what truly resonates with your users, and drive higher conversion rates across app stores.

But the key to success lies in how you run your tests. Don’t forget to test one variable at a time, have a clear hypothesis, segment traffic when possible, and allow enough time to reach statistical confidence. Use these A/B testing best practices and tools to test smarter and scale your app growth.

And lastly, if you’re ready to spy on your competitors and get ahead, start exploring AppTweak now!

Start free trial